When San Francisco’s de Young museum prepared its David Hockney exhibition a couple years ago, it didn’t just randomly slap works on its walls, leaving visitors to guess at the stories behind the offerings. A group of curators (from the Latin taking care) decided which of the artist’s “monumental paintings, Photoshop portraits, digital films that track the changing seasons, vivid landscapes created using the iPad, as well as never-before-exhibited charcoal drawings and paintings completed in 2013 ” to show, in what order and grouping. And they added the all-important museography, words that introduced the show and explained each work, its origin, story, place in the context, with occasional comments about technique or aesthetic sensibility.

Without these knowledgable and trustworthy curators (Hockney among them), the exhibition would have been far less pleasurable, it would have lacked a connection to the artist and his world.

After reading this, I hardly needed to read the rest of his post – this does a great job of reminding the reader of the value of curation. For example: why do I read Daring Fireball when I can go to each of his sources directly and bypass his intermediary status. But that would be missing the point: John Gruber does a great job of pulling out the most telling quote and commenting on it, and drawing my attention to topics that I would have otherwise missed, and drawing my attentions to new authors that I *do* want to read directly from my Feedly.

Monday Note’s Gassee goes on:

With search engines, we see a different kind of curator: algorithms. Indefatigable, capable of sifting through literally unimaginable amounts of data, algorithms have been proffered as an inexpensive, comprehensive, and impartial way to curate news, music, video — essentially everything.

And here’s where we get into a problem. The algorithm has at its disposal, if anything, too much data. Every day I get emails from Amazon recommending things related to previous purchases. If you go to Amazon for your science fiction reading, your recommendations will be irrevocably degraded if you buy even one business book or children’s book. Or household appliance. So much of this machine learning is just throwing spaghetti on the wall and hoping we’re stupid enough to eat it.

Gassee has an interesting thought -that if curation is good for music, could Apple apply a similar Herculean human curation effort to Apps? And given their volume and profit characteristics, wouldn’t it make even more sense?